Technical Field
The present invention relates to a video processing engine for facial recognition.
Description of the Related Art
Real-time video surveillance involves extraction of faces from every frame in the video streams. These faces are stored in a data store for subsequent querying (a watch-list application matches the face in the video stream against a collection of faces, also called watch-list, that is stored in a data store). To facilitate high-speed lookup of faces in the data store, it is beneficial to have an index data structure on top of the collection of stored faces. For a streaming system, it is desirable to have such an index in main memory. However, the size of the index usually grows linearly as the number of faces in the collection increase. A key challenge is to devise a new index structure such that the index not only enables sub-second look-ups, but it also either grows very slowly or remains almost constant size as the number of faces in the collection increases.
Conventional indexing methods are O(n) in space, where n is the number of entries in a collection. This is prohibitively expensive for large volumes of video data (millions of faces).
Existing indexing schemes are either all on-line, and hence in the critical path affecting performance, or all off-line, and hence do not provide up to date information affecting accuracy. The present invention aims to provide a tighter bound on index-size growth while maintaining accuracy and performance of lookups.